This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Typical approaches to validating label-free quantitative mass spectrometry use the spiking in of a limited number of proteins against a complex background proteome. However, a low number of spike-in proteins is limited in number, and is less than the expected number of proteins changed in abundance between two or more biological conditions. A convenient source of a large number of known spike-ins is that of a simpler proteome from an organism which has little peptide-level homology with the complex background. We propose to create a dataset with known levels of digested E. coli proteome spiked into a HEK293 human epithelial kidney cell proteome background which will allow us to assess the false discovery rate and quantitative accuracy of relative changes in protein abundance using a label-free approach. Also, we will qualitatively characterize the proteome of the HEK293 due to the large number of MS/MS spectra that will be acquired.